Cognitive Computing

Making a Cognitive Difference in Global Water Issues

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World Water Day, recognized annually on March 22, is about taking action to tackle the water crisis brought on mainly by globalization and the surge in population.

Freshwater scarcity is a major risk to the global economy, affecting four billion people directly. Water is a natural resource that’s core to human food and energy security, environmental health and social well-being.

The dynamics and intricacies between water, food, and energy resources on human activities, population growth, and ecosystems are complex. The decisions around the use of water, food, and energy to ensure economic growth and human security are reaching beyond human capacity. This leads to a disparity between perception verse reality in making sound policy, laws, and water investments to balance economic growth with human security.

I am optimistic that with collective action, these water challenges are solvable through the mobilization of our best expertise, resources, partnerships and state-of-the-art information. Resilient water solutions have the potential to move industry, society, and nature toward more sustainable growth, resiliency human security, and healthy ecosystems.

This will require bold thinking and imagining a more water-secure future that unlocks access to water data and information in ways we never thought possible. This begins as all great journeys, will questions that push us to think beyond what is possible. For example, what could water utilities could do if data processing time were cut in half or if they could better understand risks to take bold steps with new approaches, recognizing that there is a pattern in data that they haven’t seen before?

To start the conversation on how to solve this crisis, this week at the U.S. Water Partnership’s annual Water Leader Award Ceremony and Reception in Washington, D.C., I will represent IBM to discuss how cognitive computing and data analytics can be used to help address global water challenges. A cognitive solutions platform can analyze vast volumes of data by understanding natural language, generating hypotheses, and using human intelligence to learn as it goes. This will allow us all to reimagine the range of possibilities for accessing water data, knowledge, and information and offering solutions to global water challenges. For instance:

    • Water and wastewater utility managers could increase efficiency, save money, and reduce energy use;
    • Farmers could gain a better understanding of future precipitation variability to aid with crop planning and water conservation;
    • Entrepreneurs and technology providers could unlock new markets in the water sector and identify financing and other resources;
    • Business and government leaders could identify, understand, and mitigate water risks; and
    • Policymakers could identify trends and design data-informed, water-smart policies.

I suspect the next few years are going to be an exciting time for our industry as advancements are made for smarter energy grids, better water management, monitoring agriculture, natural disaster responses, and improving human hygiene and health.

This week IBM is taking part in a 2-day World Water Day campaign by the U.S. Water Partnership and its partners including:

  • U.S. Water Leader Award Ceremony and Reception –Scheduled for March 21, 2017 from 5:30 pm to 7:30 pm at the U.S. Institute of Peace in Washington DC, featuring the following:
  • The award presentation to Mr. Muhtar Kent, Chairman and CEO, The Coca-Cola Company.
  • Keynote remarks by Mr. Stephen Hadley, former National Security Advisor to President George W. Bush.
  • Defining a new “IBM for Water Partnership” by Mr. Brad Gammons, Managing Director, Global Energy and Utilities Industry, IBM; an effort where IBM is applying big data integration and cognitive analytics to address global water security challenges.

Bill Robertson

In order to do data analysis, there will need to be water data gathered from water sources. Even with the lowering cost of sensors, this could be expensive and time consuming.
Are there initiatives in local, state and federal government to push for this data collection?


Liang Downey

a great insight! This is something IBM can help in a great deal to leverage a variety of tool kits we have to build such cognitive system

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